Map-based routing systems are often encountered in the form of an in-vehicle device which uses a global positioning system (GPS) sensor as a basis for displaying a map of the local area surrounding the vehicle, and providing a route for the driver to follow from an origin location to a destination location. The same techniques can be used, e.g., as part of a desktop computer application, or as a mobile telephone application, to provide a user with similar mapping and routing assistance.
Regardless of the platform used, for a routing system to provide useful assistance, it must have an accurate knowledge not just of the possible routes and their distances, but of their suitability with regard to, e.g., travel time, which can be affected by factors such as traffic, or ongoing construction. Since such factors are variable, some systems gather real-time information, e.g., via traffic-monitoring devices and services, and utilize that real-time information as part of its routing determinations. Other systems determine instead a statistical likelihood of, e.g., traffic at certain times of day, and use this likelihood information as part of its routing determinations. However, each approach has its disadvantages: real-time information may be useful, e.g., at the start of a shorter journey, but is less useful for longer or more complex trips, or trips starting at a later point in time; while statistical likelihoods may be useful in planning longer or more complex trips, but may not be able to take into account unusual changes in the traffic pattern. These are the general area that embodiments of the invention are intended to address.